Flood Risk Mapping Using GIS and Multi-Criteria Analysis at Nanga Pinoh West Kalimantan Area

https://doi.org/10.22146/ijg.69879

Ajun Purwanto(1*), Rustam Rustam(2), Dony Andrasmoro(3), Eviliyanto Eviliyanto(4)

(1) Departmen of Geography Education IKIP PGRI Pontianak
(2) Departmen of Counseling Guidance Education IKIP PGRI Pontianak
(3) Departmen of Geography Education IKIP PGRI Pontianak
(4) Departmen of Geography Education IKIP PGRI Pontianak
(*) Corresponding Author

Abstract


Flood is one of the disasters that often hit various regions in Indonesia, specifically in West Kalimantan. The floods in Nanga Pinoh District, Melawi Regency, submerged 18 villages and thousands of houses. Therefore, this study aimed to map flood risk areas in Nanga Pinoh and their environmental impact. Secondary data on the slope, total rainfall, flow density, soil type, and land cover analyzed with the multi-criteria GIS analysis were used. The results showed that the location had low, medium, and high risks. It was found that areas with high, prone, medium, and low risk class are 1,515.95 ha, 30,194.92 ha, 21,953.80 ha, and 3.14 ha, respectively. These findings implied that the GIS approach and multi-criteria analysis are effective tools for flood risk maps and helpful in anticipating greater losses and mitigating the disasters.


Keywords


Flood risk;Watershed;GIS;Multi Criteria Analysis

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References

Alfieri, L., Feyen, L., & Di Baldassarre, G. (2016). Increasing flood risk under climate change: a pan-European assessment of the benefits of four adaptation strategies. Climatic Change, 136(3), 507–521.

Basri, H., & Chandra, S. Y. (2021). Assessment of infiltration rate in the Lawe Menggamat Sub-Watershed, Aceh Province, Indonesia. IOP Conference Series: Earth and Environmental Science, 667(1), 12069.

Biswajeet, P., & Mardiana, S. (2009). Flood hazard assessment for cloud-prone rainy areas in a typical tropical environment. Disaster Advances, 2(2), 7–15.

Bubeck, P., Botzen, W. J. W., & Aerts, J. C. J. H. (2012). A review of risk perceptions and other factors that influence flood mitigation behavior. Risk Analysis: An International Journal, 32(9), 1481–1495.

Chauhan, P., Chauniyal, D. D., Singh, N., & Tiwari, R. K. (2016). Quantitative geo-morphometric and land cover-based micro-watershed prioritization in the Tons river basin of the lesser Himalaya. Environmental Earth Sciences, 75(6), 1–17.

Chen, A. S., Djordjević, S., Leandro, J., & Savić, D. A. (2010). An analysis of the combined consequences of pluvial and fluvial flooding. Water Science and Technology, 62(7), 1491–1498.

Chen, A. S., Evans, B., Djordjević, S., & Savić, D. A. (2012). Multi-layered coarse grid modeling in 2D urban flood simulations. Journal of Hydrology, 470, 1–11.

Curebal, I., Efe, R., Ozdemir, H., Soykan, A., & Sönmez, S. (2016). GIS-based approach for flood analysis: a case study of Keçidere flash flood event (Turkey). Geocarto International, 31(4), 355–366.

Das, S. (2019). Geospatial mapping of flood susceptibility and hydro-geomorphic response to the floods in Ulhas basin, India. Remote Sensing Applications: Society and Environment, 14, 60–74.

Du, J., Fang, J., Xu, W., & Shi, P. (2013). Analysis of dry/wet conditions using the standardized precipitation index and its potential usefulness for drought/flood monitoring in Hunan Province, China. Stochastic Environmental Research and Risk Assessment, 27(2), 377–387.

Elkhrachy, I. (2015). Flash flood hazard mapping using satellite images and GIS tools: a case study of Najran City, Kingdom of Saudi Arabia (KSA). The Egyptian Journal of Remote Sensing and Space Science, 18(2), 261–278.

Falguni, M., & Singh, D. (2020). Detecting flood-prone areas in Harris County: A GIS-based analysis. GeoJournal, 85(3), 647–663.

Geographic, N. (2019). Floods. Available online:https://www.nationalgeographic.com/environment/ natural-disasters/floods/.

Ghimire, B., Chen, A. S., Guidolin, M., Keedwell, E. C., Djordjević, S., & Savić, D. A. (2013). Formulation of a fast 2D urban pluvial flood model using a cellular automata approach. Journal of Hydroinformatics, 15(3), 676–686.

Greene, R. G., & Cruise, J. F. (1995). Urban watershed modeling using geographic information system. Journal of Water Resources Planning and Management, 121(4), 318–325.

Haq, M., Akhtar, M., Muhammad, S., Paras, S., & Rahmatullah, J. (2012). Techniques of remote sensing and GIS for flood monitoring and damage assessment: a case study of Sindh province, Pakistan. The Egyptian Journal of Remote Sensing and Space Science, 15(2), 135–141.

Huong, H. T. L., & Pathirana, A. (2013). Urbanization and climate change impact future urban flooding in Can Tho city, Vietnam. Hydrology and Earth System Sciences, 17(1), 379.

Jamali, B., Löwe, R., Bach, P. M., Urich, C., Arnbjerg-Nielsen, K., & Deletic, A. (2018). A rapid urban flood inundation and damage assessment model. Journal of Hydrology, 564, 1085–1098.

Jha, A., Lamond, J., Bloch, R., Bhattacharya, N., Lopez, A., Papachristodoulou, N., Bird, A., Proverbs, D., Davies, J., & Barker, R. (2011). Five feet high and rising: cities and flooding in the 21st century. World Bank Policy Research Working Paper, 5648.

Khosravi, K., Pham, B. T., Chapi, K., Shirzadi, A., Shahabi, H., Revhaug, I., Prakash, I., & Bui, D. T. (2018). A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran. Science of the Total Environment, 627, 744–755.

Komolafe, A. A., Awe, B. S., Olorunfemi, I. E., & Oguntunde, P. G. (2020). Modeling flood-prone areas and vulnerability using the integration of multi-criteria analysis and HAND model in the Ogun River Basin, Nigeria. Hydrological Sciences Journal, 65(10), 1766–1783.

Liu, J., Gao, G., Wang, S., Jiao, L., Wu, X., & Fu, B. (2018). The effects of vegetation on runoff and soil loss: Multidimensional structure analysis and scale characteristics. Journal of Geographical Sciences, 28(1), 59–78.

Liu, Y., Cui, Z., Huang, Z., López-Vicente, M., & Wu, G.-L. (2019). Influence of soil moisture and plant roots on the soil infiltration capacity at different stages in arid grasslands of China. Catena, 182, 104147.

Lyu, H.-M., Shen, S.-L., Zhou, A., & Yang, J. (2019). Perspectives for flood risk assessment and management for the mega-city metro system. Tunneling and Underground Space Technology, 84, 31–44.

Mahmoud, S. H., & Gan, T. Y. (2018). Urbanization and climate change implications in flood risk management: Developing an efficient decision support system for flood susceptibility mapping. Science of the Total Environment, 636, 152–167.

Mandal, S. P., & Chakrabarty, A. (2016). Flash flood risk assessment for upper Teesta river basin: using the hydrological modeling system (HEC-HMS) software. Modeling Earth Systems and Environment, 2(2), 59.

Meyer, V., Haase, D., & Scheuer, S. (2009). Flood risk assessment in European river basins—concept, methods, and challenges exemplified at the Mulde River. Integrated Environmental Assessment and Management, 5(1), 17–26.

Nagu, N., Lita, A. L., Bebi, H., & Wahiddin, N. (2021). GIS Based Method for Flood Hazard Assessment in Kobe River Watershed-North Maluku Province. E3S Web of Conferences, 328, 4019.

Ozkan, S. P., & Tarhan, C. (2016). Detection of flood hazard in urban areas using GIS: Izmir case. Procedia Technology, 22, 373–381.

Paudyal, G. N. (1996). An integrated GIS-numerical modeling system for advanced flood management. Proceeding of the International Conference on Water Resources and Environment Research: Towards the 21st Century, Kyoto University, Japan, 555–562.

Petit-Boix, A., Sevigné-Itoiz, E., Rojas-Gutierrez, L. A., Barbassa, A. P., Josa, A., Rieradevall, J., & Gabarrell, X. (2017). Floods and consequential life cycle assessment: Integrating flood damage into the environmental assessment of stormwater Best Management Practices. Journal of Cleaner Production, 162, 601–608.

Pradhan, B., Shafiee, M., & Pirasteh, S. (2009). Maximum flood-prone area mapping using RADARSAT images and GIS: Kelantan river basin. International Journal of Geoinformatics, 5(2).

Radmehr, A., & Araghinejad, S. (2015). Flood vulnerability analysis by fuzzy spatial multi-criteria decision making. Water Resources Management, 29(12), 4427–4445.

Rincón, D., Khan, U. T., & Armenakis, C. (2018). Flood risk mapping using GIS and multi-criteria analysis: A greater Toronto area case study. Geosciences, 8(8), 275.

Roy, S., Bose, A., & Chowdhury, I. R. (2021). Flood risk assessment using geospatial data and multi-criteria decision approach: a study from historically active flood-prone region of the Himalayan foothill, India. Arabian Journal of Geosciences, 14(11), 1–25.

Rozalis, S., Morin, E., Yair, Y., & Price, C. (2010). Flash flood prediction using an uncalibrated hydrological model and radar rainfall data in a Mediterranean watershed under changing hydrological conditions. Journal of Hydrology, 394(1–2), 245–255.

Sahana, M., & Patel, P. P. (2019). A comparison of frequency ratio and fuzzy logic models for flood susceptibility assessment of the lower Kosi River Basin in India. Environmental Earth Sciences, 78(10), 1–27.

Shafapour Tehrany, M., Shabani, F., Neamah Jebur, M., Hong, H., Chen, W., & Xie, X. (2017). GIS-based spatial prediction of flood-prone areas using standalone frequency ratio, logistic regression, evidence weight, and ensemble techniques. Geomatics, Natural Hazards, and Risk, 8(2), 1538–1561.

Silalahi, F. A., Zainabun, Z., & Basri, H. (2019). Kajian Sifat Fisika Tanah pada Lahan Budidaya Sub DAS Krueng Jreu Kabupaten Aceh Besar. Jurnal Ilmiah Mahasiswa Pertanian, 4(2), 457–463.

Skilodimou, H. D., Bathrellos, G. D., Chousianitis, K., Youssef, A. M., & Pradhan, B. (2019). Multi-hazard assessment modeling via multi-criteria analysis and GIS: a case study. Environmental Earth Sciences, 78(2), 47.

Supriyadi, T. (2020). banjir rendam-ribuan-rumah-warga-di-melawi-1-jembatan-gantung-roboh. Liputan 6. www.liputan6.com/regional/read/4355878/

Suryadi, U. E., & Riduansyah, B. (2021). LAJU INFILTRASI PADA BEBERAPA PENGGUNAAN LAHAN DI DESA PAK MAYAM KECAMATAN NGABANG KABUPATEN LANDAK. Jurnal Sains Mahasiswa Pertanian, 10(1).

Tehrany, M. S., Pradhan, B., & Jebur, M. N. (2013). Spatial prediction of flood susceptible areas using rule-based decision tree (DT) and a novel ensemble bivariate and multivariate statistical models in GIS. Journal of Hydrology, 504, 69–79.

Ullah, K., & Zhang, J. (2020). GIS-based flood hazard mapping using relative frequency ratio method: A case study of Panjkora River Basin, eastern Hindu Kush, Pakistan. Plos One, 15(3), e0229153.

Youssef, A. M., Pradhan, B., & Hassan, A. M. (2011). Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS-based morphometry and satellite imagery. Environmental Earth Sciences, 62(3), 611–623.

Zhang, J., & Chen, Y. (2019). Risk assessment of flood disaster induced by typhoon rainstorms in Guangdong Province, China. Sustainability, 11(10), 2738.

Zhang, N., Luo, Y.-J., Chen, X.-Y., Li, Q., Jing, Y.-C., Wang, X., & Feng, C.-H. (2018). Understanding the effects of composition and configuration of land covers on surface runoff in a highly urbanized area. Ecological Engineering, 125, 11–25.

Zhang, S., & Pan, B. (2014). An urban storm-inundation simulation method based on GIS. Journal of Hydrology, 517, 260–268.

Zhou, Q., Su, J., Arnbjerg-Nielsen, K., Ren, Y., Luo, J., Ye, Z., & Feng, J. (2021). A GIS-Based Hydrological Modeling Approach for Rapid Urban Flood Hazard Assessment. Water, 13(11), 1483.

Zwenzner, H., & Voigt, S. (2009). Improved estimation of flood parameters by combining space-based SAR data with very high-resolution digital elevation data. Hydrology and Earth System Sciences, 13(5), 567–576.



DOI: https://doi.org/10.22146/ijg.69879

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